Color-Based Road Sign Detection and Tracking

Abstract

Abstract. This paper describes a general framework for the detection and tracking of traffic and road signs from image sequences using only color information. The approach consists of two independent parts. In the first we use a set of Gaussian distributions that model each color for detecting road and traffic signs. In the second part we track the targets detected in the first step over time. Our approach is tested using image sequences with high clutter that contain targets with the presence of rotation and partial occlusion. Experimental results show that the proposed system detects on average 97% of the targets in the scene in near real-time with an average of 2 false detections per sequence.

Real-Time Road Signs Recognition Using Mobile Gpu

“…The article [6] shows that tracking helps perform localization faster. However, these algorithms have greater computational complexity and cannot be used in real-time.…”

Trends Towards Automotive Electronic Vision Systems for Mitigation of Accidents in Safety Critical Situations

“…For example, road-sign recognition is becoming a popular application (Lopez & Fuentes, 2007). Poor weather conditions can also be detected (Kurihata et al, 2005).…”

Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

“…Then in the classification stage, the detected road sign candidates are assigned to the class that they belong. For the detection stage, there are color based detection (Lopez and Fuentes, 2006), shape based detection (Loy and Barnes, 2004) and the combination of the two approaches (Adam and Ioannidis, 2014). Detection stage is very important because the road signs that are not detected during this step is not available to be recovered later.…”